ecological purchase intentions

Erasmus University Rotterdam| Rajiv Hanoeman

Ecological Purchase Intentions Do consumers actually care about the environment?

Master Thesis

Program: Economics and Business

Specialization: Marketing

Rajiv Hanoeman

Student number: 313087

Thesis supervisor: Drs. N. Hofstra

July, 2013


Abstract

Consumers of the world have been made more aware of environmental issues that have risen

during this time. The shift towards environmental behaviour has been in part due to the

popularity rise in ecological awareness. Studying environmental behaviour is a popular subject

in the academic field. Many researchers investigated the motives what drives one to act this

way. Although a great amount of studies have been done on behaviour, very little has been

written primarily on ecological purchase intentions. This paper aims to contribute to that scarce

research. A sample of 2668 respondents was utilized to determine whether consumers actually

care about a sustainable environment and which factors influence their ecological purchase

intentions. The factors environmental attitude, perceived responsibilities and age were applied

to measure these intentions. Several variables were linked to these factors. The variables of

environmental attitude and age had the largest impact on ecological purchase intentions, with

the need to talk as the strongest predictor. The results reflected that according to the consumers

themselves, they value a sustainable environment. However, the environmental concerns are

not consistently translated to their actual intentions.


Preface & acknowledgements

Fascinated and inspired by environmental documentaries of Tegenlicht (Dutch) and the non-

profit organisation the Story of Stuff, my interests and willingness to act in the environmental

field rapidly grew. Hence the decision to write about ecological purchase intentions was not a

difficult choice to make. Despite several setbacks and challenging times I encountered during

the thesis period, I am glad to eventually contribute to this field.

My thesis supervisor Nel Hofstra is also a big inspiration for environmental consciousness.

I sincerely felt privileged to have her as my supervisor, I am grateful for the guidance that she

provided during this period. My thanks also go to Luit Kloosterman for providing the dataset for

this research.

Furthermore, my thanks go to my family and friends who supported me. I would also like to

thank my classmate and friend Leonaris Rey for motivating and accompanying me when I went

to the University to work on my thesis. Most of all I want to thank my parents, brother Kishan

Hanoeman and sister Natasha Hanoeman for believing in me. Their positive energy guided me

through my academic career.

“Be the change that you wish to see in the world.”

- Mahatma Ghandi -

Rajiv D. Hanoeman

August, 2013


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Table of Contents

Chapter 1 Introduction .............................................................................................................................. 3

1.1 Managerial relevance................................................................................................................................ 4

1.2 Relevant Research.................................................................................................................................... 6

1.3 Research questions .................................................................................................................................. 8

Chapter 2 Theoretical Background ....................................................................................................... 10

2.1 Green versus Ecological ......................................................................................................................... 10

2.2 Theory of planned behaviour.................................................................................................................. 10

2.3 Environmental attitude ............................................................................................................................ 12

2.4 Perceived responsibility .......................................................................................................................... 13

2.5 Ecological consumer ............................................................................................................................... 15

2.5.1 Demographic factor: Age................................................................................................................. 17

2.6 Hypotheses .............................................................................................................................................. 18

Chapter 3 Methodology and Dataset .................................................................................................... 19

3.1 Conceptual Framework ........................................................................................................................... 19

3.2 Measures ................................................................................................................................................. 20

3.3 Sample and data description .................................................................................................................. 21

3.3.1 Environmental attitude variables..................................................................................................... 22

3.3.2 Perceived responsibility variables .................................................................................................. 24

3.3.3 Age variable ..................................................................................................................................... 26

3.3.4 Dependent variable.......................................................................................................................... 26

3.4 Data analyses .......................................................................................................................................... 27

3.4.1 Data preparation .............................................................................................................................. 27

3.4.2 Normal distribution ........................................................................................................................... 27

3.4.3 Correlation analysis ......................................................................................................................... 29

3.4.4 Multiple regression analysis ............................................................................................................ 30


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Chapter 4 Results..................................................................................................................................... 32

4.1 Correlation results ................................................................................................................................... 32

4.2 Multiple regression results ...................................................................................................................... 33

4.3 Overview of results.................................................................................................................................. 35

Chapter 5 Conclusion .............................................................................................................................. 37

5.1 Limitations ................................................................................................................................................ 38

5.2 Recommendations for further research ................................................................................................. 39

References ................................................................................................................................................... 40

Appendix ................................................................................................................................................... 44

Appendix 1: Questionnaire ........................................................................................................................... 44

Appendix 2: Frequency tables SPSS output ............................................................................................... 46

Appendix 3: Normal distribution plots & table.............................................................................................. 48

Appendix 4: Correlation table ....................................................................................................................... 50

Appendix 5: Regression tables ..................................................................................................................... 51


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Chapter 1 Introduction

Over the past few decades, consumers of the world have been made more aware of

environmental issues that have risen during this time. They have been made aware of these

issues in increasing levels in areas that are unavoidable to the up-to-date citizen. Areas such as

the media (McIntosh, 1991), increased number of environmental groups (Tapon and Leighton,

1991), and stricter laws pertaining to the environment both nationally and internationally

(Charter, 1992) can be considered. In one way or another all can be seen as significant.

This is important, because consumers themselves are heavily involved as factors in

environmental pollution, as there are many consumption patterns that link back to ecological

damage (Balderjahn, 1988). It has been found that specific demographics, personality, human

values and attitude variables can be used for grouping ecologically-concerned consumers.

Balderjahn’s research on this focused on understanding what determined a consumer’s

ecological consciousness, using predictors based on the above-mentioned variables as well as

theoretical frameworks based on prior research on ecological-concerned consumers.

The United Nations also determined that the biggest cause of deterioration of the global

environment is the unsustainable pattern of consumption and production, mainly in

industrialized countries (UNEP, 2001). The plan of action that the UN created and intended to

use globally, called Agenda 21, contained the above statement. Despite the advancement in

human development, with the increase of consumption it results in environmental degradation

(Thompson et al., 2010). One of the solutions to this was stated in Agenda 21, called

sustainable consumption, and is defined as the consumption of goods and services that satisfy

the needs of the present generations without compromising the needs of the future ones

(Heiskanen and Pantzar, 1997).

In the past few years, these areas added to the concerns of the public, the top issues being

mainly about the quality of water, hazardous / toxic waste, pollution from public and private

transportation, deforestation, and more, just to name a few (Ottman, 2011, The New Rules of

Green Marketing).


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1.1 Managerial relevance Ottman (2011) continues into discussing various points where companies can make use of

these turn of events for consumers wanting to go green, noting them as business opportunities.

Due to the growing demand for green products and services by consumers, businesses

themselves can promote themselves as green companies offering greener products and

services than their competitors. This in turn enhances their sales, their image, and gives the

employees and the company on a whole a boosted morale to uphold.

With the concept of a premium cost increase for a green good over a regular version of a good,

consumers that are willing to green are prepared to pay extra. There are sceptics that require

proof through research before making the extra investments for the extra costs of introducing

new green products. For those willing to buy however, accept the premium price because

expectations have grown over the years, and environmental friendliness can be seen as an

additional measure of quality for products.

Along with this new measure of quality, green products also can offer consumer benefits which

can also be marketed as additional advantages on top of being greener than the competition.

Ottman (2011) listed benefits such as compact fluorescent light bulbs saving more money while

used and last longer at the same time, hybrid cars running near silently and gives the driver a

green image and organic produce being safer and having better taste.

Another benefit to striving to go green is that it is a new source of innovation according to

Ottman. Going green and creating opportunities to go green is doing something new in itself,

and in order to stand out from the competition, you will need to create green technologies,

business models and designs. These will bring attention to your company through new

customers as well as the public eye and create new competitive advantages that also show that

your company is moving with the current times and trends, as well as staying ahead of the

curve. Some examples given by Ottman include Toyota converting vehicle manufactories that

were truck- and SUV-focused to manufacture hybrid-engine vehicles, and in-home energy

meters that allow you to monitor your energy use within your home.

Ottman did however focus on the other side of greener products, which can in fact lead to

increased costs for manufacturing. For example, greener packaging in a different size causing

issues with shipping crate sizes, or even extra costly activities, such as transporting waste in


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bulk to be recycled. This is the reason behind the use of the tool called life-cycle assessment

(LCA), and it assesses all of the steps and issues involved with creating a greener product. The

assessment focuses on four main topics: raw materials acquisition and processing,

manufacturing and distribution, product use and packaging and after-use/disposal. With

conducting an LCA, decisions have to be made in the process over things. For example,

deciding whether to look at the product alone or include its packaging. Other issues to keep

account for are those that the consumer has to add themselves to the product in order to

function throughout its lifetime or the waste from the transportation of the product. This

assessment is very crucial to keep in mind when making the decision to make greener products

because realistically-speaking, it is not an easy or cheap conversion.

Chen and Chang (2012) also agree with the idea that companies should apply green marketing

strategies to increase the value of their products to customers and environmental watchers,

which in turn also increased their competitive advantage in this regard. They state that as green

products are more popular in markets today, green marketing is more common and the

companies going along with this are seen to be more in tune with current trends. These

marketing activities include creation and promotion of products that meet customer’s needs in

terms of environmental care. Not only does a company stand out more on their own compared

to other non-green companies when they use green marketing, but they can create new rules in

their market through their green marketing. Peattie (1992) repeats that consumers are willing to

buy greener products that have been proven through research to be safer for the environment,

and therefore stated that companies should provide this reliable proof to reduce customer’s

perceived risk. Even though it can be hard to provide this information, it is a must to do so to win

their trust.

Chen (2008) listed the five following reasons for companies to adopt green marketing:

Utilizing green opportunities.

Increasing corporate images.

Raising product value.

Enhancing competitive advantages.

Complying with environmental trends.

It is also noted by Chen (2012) that executing green marketing can raise consumer purchase

intentions. There are potential consumers that have a view about greener goods being of lower


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quality or do not deliver on promises for the environmental safety. Also, consumers may not

agree on attributes that depend on taste or opinion, such as value, quality, price and

performance. The best way to get consumers to see those attributes as superior in the greener

product is to compare them to non-green products, and to enhance consumer purchase

intentions, greenness and high-quality attributes need to be combined. Reducing consumer

perceived risk about how they feel negatively about greener products can ease their doubts and

raise their trust.

Balderjahn (1988) determined that in order to develop ecologically appropriate market

segmentation strategies, a proper identification and description of an ecologically-concerned

consumer is needed for both private and public sectors. These segmentation strategies can

help companies know how to better position their greener good in order to appeal more to

consumers. Regardless, it is best for the manufacturers to clearly show that the product does

not harm the environment and that purchase and usage of the product contributes to

environmental damage reduction.

Finally, Grimmer and Bingham (2013) state that some consumers seek to buy goods based on

a company’s role in society and its level of environmental responsibility. Therefore it is a major

point to go green for a company, and to make sure that it is known to the public and market. In

2008, green consumers had an annual buying power of $500 billion worldwide (Ferraro, 2009).

Even in the years of the financial crisis of 2008, spending for greener goods and services

increased by 18% over the two years of the crisis (The Co-operative Bank, 2010). Focusing on

the UK alone during the crisis showed that the green market grew from £36.5 billion in 2007 to

£43.2 billion in 2009. These figures show that due to the growth in green expenditure reflect that

consumers have a positive attitude towards greener products, and included greener options into

their purchasing decisions according to Maignan and Ferrell (2004) and Vermillion and Peart

(2010).

1.2 Relevant Research Research has been conducted in the past about ecological behaviour, and one important piece

of research was conducted by Fraj and Martinez (2007) where it focused on environmental

attitudes as meaningful predictors of ecological behaviour. They found that consumers

increasingly choose ecological products when they shop because of them being healthier


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options and the help they give in sustaining the environment for the future. Consumers are

prepared to abandon harmful goods and make the switch to greener goods, and companies are

aware of how important it is to reflect that in the developing and marketing of their green goods.

They developed a conceptual model and framework and found that environmental attitudes

have a significant effect on ecological behaviour. Their research helped them to understand how

consumers feel and how their attitudes best define their behaviour in relation to environmental

problems.

Barr (2003) conducted research on whether environmental action is influenced by a number of

factors, such as environmental values, situational characteristics and psychological variables.

This research began because of the increase in interest in how people could be encouraged to

be more ecological at home. The factors mentioned before were found to be crucial in

promoting environmentally responsible behaviours like saving energy and waste recycling.

With the above-mentioned research papers, it shows the most similar research done to this

paper, but more papers came across what is considered a consumer paradox when it comes to

what they think about the environment, and what they actually do to help it.

Diekmann and Preisendörferer (1998) found that it was shown that there are considerable

inconsistencies between society’s environmental attitudes and their behaviour. They look at and

dissect the concept of environmental behaviour from two separate views to get a better

understanding of these inconsistencies. They found three strategies that these two views have

in common, which were shifting attention, low-cost, and subjective-rationality. Even despite a

high degree of consciousness for the environment, it was found that everyday experience

pointed to obvious inconsistencies between verbal claims and actual behaviour, with behaviour

following traditional lines of action.

Wong et al. (1996) and Aspinall (1993) found a paradox as well, that despite the increase in

society’s sympathy towards the environment, environmentally-friendly products had not

achieved the expected level of market success. Kalafatis et al. (1999) noted that in many

consumer product categories, environmentally-friendly producers had achieved disappointingly-

low levels of market share.


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This finding was supported by the findings of UK surveys that showed that although consumers

had increasing concerns with the environment’s state of being, even at a decreasing rate, their

willingness to buy environmentally-friendly products had dropped.

Grimmer and Bingham (2013) also make note that despite increased interest, evidence for the

impact of the environmental initiatives on consumer behaviour is both contradictory and

equivocal. The actual size of the green market despite the growing talk of trends has been

questioned as well (Papaoikonomou et al., 2011). Cowe and Williams (2000) refer to the 30:3

syndrome, which meant that while 30% of consumers may say that they are concerned about

firms’ social responsibility, green goods account for 3% of the market share at the most.

Polonsky (2011) talked about how green marketing is not reaching its potential for influencing

consumer behaviour as well as improving the environment. Carrington et al. (2010) notes that

even though the number of consumers that proclaim to be motivated by social and

environmental issues grow, there is evidence that shows that the translation to actual

consumption is less obvious. Devinney et al. (2010) shortly puts it that the green consumer is

mythical to them.

1.3 Research questions The contradictions stated in the preceding paragraph might raise questions if consumers

actually appreciate a sustainable environment. It has been shown above that although the

consumers might say they care about the environment, the results of the previously mentioned

studies show otherwise. The consumers’ paradox will also be studied in this paper.

In the previous paragraph it is also stated that several studies have been conducted on

environmental behaviour. This is a very broad topic, including recycling, waste management,

consuming etc. The current paper therefore will only focus on purchase intentions instead of

behaviour.

The goal of this paper is to examine how certain factors affect the ecological purchase

intentions of consumers. Not many studies exist about ecological purchase intentions, despite

being mentioned in numerous papers. In this way, the research will contribute to scarce

research in a growing market.


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Based on the initial findings, the actual value of a sustainable environment to consumers seems

questionable. By measuring ecological purchase intentions, this can be tested. Therefore, the

research question of this thesis will be:

“Do consumers value a sustainable environment and which factors affect their ecological purchase intentions?”

The following sub research questions will support to answer the main question:

Does a positive environmental attitude affect ecological purchase intentions?

Do perceived responsibilities affect ecological purchase intentions?

Does age influences ecological purchase intentions?


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Chapter 2 Theoretical Background

2.1 Green versus Ecological Nowadays the term green is often used to indicate environmental concerns. Green can be

described as a descriptor, for a good or service for example, which inflicts reduced or minimum

or no harm to the environment. It is used by companies in green marketing for their goods and

services to emphasize that they have an environmentally-safer alternative to others in the

market. The level of green can vary from a slight change compared to a regular good, to a

completely environmentally-friendly process of creation until shipping that does no harm at all to

the environment.

Looking at the definition of ecological and it is a deeper, more meaningful representation of what

is needed for the environment. The Merriam-Webster dictionary1 defines ecological as “the

study of the relationship between organisms and their environment”, in this case, organisms

pertain to humans specifically. Another description2 states that it is “the branch of sociology that

is concerned with studying the relationships between human groups and their physical and

social environments”. A third description2 states that it is “the study of the detrimental effects of

modern civilization on the environment, with a view towards prevention or reversal through

conservation”. This third description is the one that this research paper will side with, and is the

reason why ecological is used in the research question instead of green. Since there is no

vague measurement involved, the goal is clear to preserve or reverse the damage done to the

environment.

2.2 Theory of planned behaviour This paper uses the theory of planned behaviour based on the original thought process, the

theory of reasoned action, or TRA, written by Fishbein & Ajzen (1975). The idea behind this

theory is that consumer’s attitudes and subjective norm towards environmental issues can steer

them towards greener purchases for the sake of the environment. The model for TRA is

supported and has been cited by many research papers linked to consumer behaviour literature

where the goal was to predict intentions. One paper that used TRA in such a manner was by

Lee and Green (1991). TRA was also used to determine the behaviour of consumers in the 1 http://www.merriam-webster.com/dictionary/ecology 2 http://www.thefreedictionary.com/ecological


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research done by Mostafa (2007) and Mei et al. (2012). The main reasons TRA was acceptable

to use in those papers was a combination of the following assumptions: that purchase intentions

were based on the consumer’s preference, that consumers are rational and use the information

available to them as a basis for their choice, and that consumers consider the consequences of

their choice of product purchased (Dodd, 2010; Fishbein and Ajzen, 1975).

With that brief insight into the predecessor of the theory of planned behaviour, Ajzen (1985) took

TRA and expanded it past the limiting factor of looking at consumer preference (volitional

control). This was done by including beliefs in relation to the possession of necessary resources

and opportunities for performing a certain behaviour (Madden, 1992) and the thought that the

more resources and opportunities a consumer thinks that they have, the greater the perceived

behavioural control over their behaviour.

This perceived behaviour control is a variable that is added to the existing model of TRA which

has a direct effect on behaviour and an indirect effect on behaviour via intentions. This indirect

behaviour implies that when a consumer feels that they have little control over doing what they

want to do because of a lack of resources, then they have low motivation to do the action even if

they believe that doing the action is a good thing (Madden, 1992). Consumers’ behaviour is

strongly influenced by the confidence they have in their ability to perform the behaviour

(Bandura et al., 1980). This, according to them, is why the indirect link from perceived

behavioural control to intentions is a reflection of the motivational influence of control on

behaviour via intentions. The other link to perceived behaviour control from behaviour is a direct

link that reflects the actual control that a consumer has over their actions.

Ajzen and Madden (1986) completed their first test of this theory with students’ class

attendance, where the results showed that perceived behaviour control was a significant

predictor of intentions after controlling for attitudes and subjective norms. But on the contrary,

perceived behavioural control did not contribute to the prediction of target behaviour after

controlling for intentions. This shows with the significant level of response that intentions are a

far better connection for predictions than with predicting behaviour.

Oreg and Katz-Gerro (2006) built on Ajzen’s theory by testing a model that predicted pro-

environmental behaviour with the addition of Inglehart’s and Schwart’s individual works on value

dimensions. Inglehart’s postmaterialistic values showed to be the more significant of the two,


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affecting environmental concern, leading to environmental concern, perceived threat and

perceived behavioural control affecting willingness to sacrifice, affecting a number of pro-

environmental behaviours.

Kalafatis et al. (1999) also used Ajzen’s theory as a conceptual framework for their paper on

cross-market examination with green marketing. Their result showed that there was significant

support for the robustness in explaining intention, while the theory varied in accordance to

behaviour depending on how established and clearly-formatted the market was. This is yet more

proof that intentions should be used in measurements over behaviour.

In short, the theory of planned behaviour would predict two possible effects of perceived

behavioural control on behaviour, where perceived behavioural control firstly reflects

motivational factors which have an indirect effect on behaviour through intentions, and secondly

where it reflects actual control with a direct link to behaviour independent of intentions.

2.3 Environmental attitude Eilam and Trop (2012) defined environmental attitude as a requirement for achieving

environmental behaviour. An analysis was made between pro-environmental attitudes and

behaviour, where intention to act was a determinant of pro-environmental behaviour. This

intention to act was a factor made up of variables, including attitudes. A 1993 survey used by

Eilam and Trop (2012) found high levels of environmental attitudes and low levels of

environmental behaviour. This finding did not give the feeling of a positive conclusion as in the

end, it is action that makes a difference. Kinnear et al. (1973) stated that a buyer’s attitude has

to express their concern for ecology. It was also written that attitudes have served as predictors

of energy conservation behaviour, ecologically-conscious purchasing and product use and

recycling.

Balderjahn (1988) stated that other researchers had found that specific factors, including

attitudinal variables were useful for characterizing ecologically-concerned consumers. Dersken

and Gartrell (1993) had concluded in their research that environmental attitudes affect recycling

behaviour only where a structured recycling program existed. Guagnano et al. (1995) also

looked into recycling behaviour, with attitude theories decreasing in predictive value as more

external factors came into play.


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The research conducted by Fraj and Martinez (2007) focused on environmental attitudes as

meaningful predictors of ecological behaviour. They concluded that environmental attitudes

have a significant effect on ecological behaviour, and learned more about what attitudes define

their behaviour in relation to environmental problems.

These theory discussions from paragraph 2.2 and 2.3 lead into the first hypothesis for this paper

to solve, which is:

H1: A positive environmental attitude enhances ecological purchase intentions

2.4 Perceived responsibility The first trace of the concept of perceived responsibility comes from the paper of Kinnear et al.

(1973) where perceived consumer effectiveness was identified and was created as a measure

to see how far a person believes an individual consumer can be effective in pollution reduction.

Henion and Wilson (1976) take this measure and expand it to determine that the ecologically-

concerned consumer is an internally-controlled individual, and this concept is a strong predictor

for their perception of economic problems.

Mei et al. (2012) discuss perceived responsibility by first looking at government initiative. It

refers to the initiative taken by the national government or the support given by the national

government (Diekmeyer, 2008). Diekmeyer stated that the role of the government in

environmental protection is undeniable, and as the role model to its country, they should lead by

example in organizing sustainability programs. By leading, the government should initiate and

promote sustainable events to the community to bring about sustainability awareness to its

society (Mei et al., 2012). Chen and Chai (2010) mentioned an example of a government

leading by example with the Malaysian government publicizing various strategies to implement

sustainable consumption and development. Haron et al. (2005) also used Malaysia as an

example by using social advertisement to educate their people about environmental awareness

and concern.

Mei et al. (2012) mentioned peer pressure in their paper, and this research uses their stand on it

as an addition to perceived responsibility. Cohan’s (2009) take on perceived responsibility

referred to the psychological pressure that each person experienced when comparing their


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actions with others, or in other words, peer pressure. He states that it was clear that supplying

people with information was not enough to create a change in behaviour. Peer pressure by not

following the same decision as others in their surrounding could cause a large behavioural shift,

thus changing their surrounding could change that person’s mindset (Daido, 2004). Social

influence was also mentioned in regards to perceived responsibility as whether an action should

or should not be performed by someone in another’s point of view (Kalafatis et al., 1999). Social

influence was found by Lee (2008) to be the top predictor of young consumer purchasing

behaviour in Hong Kong. Also mentioned and argued was that social influence was the top

factor in defining purchase intentions for environmental goods in the UK (Kalafatis et al., 1999).

Stern et al. (1995) stated the importance of looking into the social structure that individuals are

situated in, based on their concept of social structures shaping the individuals that exist in them.

The theory behind this is that these social structures shape individuals’ experiences, leading to

shaping their personal values, beliefs and behaviours. Oreg and Katz-Gerro (2006) determined

that individuals’ environmental attitudes and behaviour are not only determined by

socioeconomic logic but also by the peer pressure of cultural values.

This research saw a correlation with perceived responsibility and social responsibility with the

research conducted by Thompson et al. (2010) where it was found that social responsibility is

the concept where businesses are obliged to handle society’s welfare further than the

requirements of society. These obligations include minimizing harmful impacts to the

environment, and should ideally be managed as a whole, rather than as individual undertakings.

A company cannot think about the creation of an ecological product without considering how

every factor involved in creating the product impacts the environment, in other words, the entire

product life cycle (Wasik, 1996).

Specifically, firms have been increasingly noticeable to the public in terms of environmental

issues in part due to environmental disasters caused by industrial manufacturers around the

world (Chen, 2011). This unwanted exposure to the public and mainstream reputation has

resulted in more companies making themselves more ecological in terms of image and

infrastructure, also due to the rising concerns of global warming (Molina-Azorí et al., 2009;

Haden et al., 2009). This shows that firms should apply green marketing strategies to enhance

the perceived value of their company and products in light of the rise in environmental

awareness, and in turn, increase their competitive advantage with competitors (Chen and


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Chang, 2012). To successfully sell their eco-friendly products to the public, companies should

provide reliable information to customers willing to buy green products with trustworthy

information that reduces their perceived risk (Peattie, 1992).

Eilam and Trop (2012) looked at how the role of acquisition of environmental behaviour was

explained by the assumption that changes on a personal level can lead to changes on a societal

level for sustainability. In short, if everyone acts environmentally-minded, society will act

environmentally safe. Fraj and Martinez (2007) briefly mention that people are aware that

environmental protection is not only up to firms and institutions but also their own responsibility

as consumers. Diekmann and Preisendörfer (1998) discussed the differences with aspirations

and reality, where many conferences deal with environmental issues but fail to meet

expectations. Next, it was discussed about national governments having restrictive funding for

environmental agencies, and political parties using promises for environmental policies with no

real effort to carry them out. Finally, at the individual citizen-level, they note that aspirations and

reality do not appear to co-exist together.

Despite the research made in perceived responsibilities shown in this subchapter, consumer

perceived responsibility has not been measured in most papers. This study can contribute a

new factor to intentions by testing with the following hypotheses:

H2a: Perceived social responsibility influences ecological purchase intentions

H2b: Perceived corporate responsibility influences ecological purchase intentions

H2c: Perceived governmental responsibility influences ecological purchase intentions

2.5 Ecological consumer Brooker (1976) discussed an early concept of the ecological consumer, the socially conscious

consumer. The paper concluded that individuals who are higher in self-actualization are more

likely to be ecological consumers over those with lower levels. This meant that as the person

becomes psychologically healthier, the likelier this person will take action for the sake of

society/the environment. The use of ecological products shows that there is concern for the

preservation of a healthy environment, although the results aren’t immediately seen. The

ecological consumer must be one that is willing to bear the possible extra costs of these

ecological products, and assume the value of the future benefits of the environment. This also


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includes passing on alternative, cheaper goods that are more harmful to the environment. This

target group of consumers is also perfect for other products to help other various types of social

problems.

Thompson et al. (2010) continues with their interpretation using green consumerism, where if

corporations are to continue using environmental marketing strategies, consumers must willing

to buy the green goods they are marketing. Therefore, gaining an understanding of an

ecological consumer is crucial. Kilbourne et al. (2002) state that there isn’t a clear agreement of

ecological consumers and what they want, will do or how to measure them. Peattie (2001)

reached a universally-accepted explanation for ecological consumer behaviour - it will occur

when concern for the environment translates into ecologically conscious consumer behaviour.

Most of the ecological consumer behaviour researchers try to categorize ecological consumers

by linking various variables with consumers that show ecologically-conscious consumer

behaviour (Thompson et al., 2010).

Ecological consumers are pictured to make ecological purchasing decisions according to two

purchase characteristics. These are the will to change to buy a green good, and the confidence

in this green good (Peattie, 2001). In these goods, there is an imbalance of information between

the consumer and the company making the good. According to Akerlof (1970), this often results

in consumer confusion or ignorance in regards to the range of quality of goods in the market.

One of the things that causes this is how green goods have qualities that cannot be evaluated

or experienced before purchasing them (Karstens and Belz, 2006). An example of green usage

that has wide appeal is the use of recycled, eco-friendly paper, because it does not differ much

in price from other paper, and the confidence is high in this type of good.

Another definition of an ecological consumer is from the research by Renfro (2010), where it

was defined as a consumer who supports businesses that are run in environmentally-friendly

ways. The ecological consumer is also concerned about how green the purchased good is as

well.

Mei et al. (2012) listed attributes that an ecological consumer could have:

Most-likely well-educated young adult women with more money to spend

They will expect green products to function as well as non-green products, and aren’t willing

to pay too much extra or give up too much quality


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Will not solely buy a green product just for the environmental benefits alone, must still meet

their basic needs in a product

Will be likelier to respond to product attributes that benefit them personally

Are not willing to take one much extra inconvenience with using the green product, or make

extra effort to purchase the product over a non-green product

Are not expecting a perfectly-green product for the environment, but are looking for active

movements in environmental benefits, backed by facts

Each of these attributes was listed with a possible implication for the green marketing that

corresponded with each attribute, with a solution for each of them as well. Lu et al. (2010) talked

about consumer trust positively affect consumer purchase intentions, and when focusing on

ecological consumers, it would imply that ecological trust of goods would positively affect their

ecological purchase intentions. Thompson et al. (2010) also showed a similar stance by saying

that if a consumer does not have confidence in the green good having a meaningful influence,

they are less likely to have a preference for green goods in general. This is once again crucial

for marketers to make clear so that ecological consumers can have confidence in the benefits of

the ecological good.

2.5.1 Demographic factor: Age Thompson et al. (2010) talked about prior research, namely Straughan and Roberts (1999) and

Rowlands et al. (2003) stating that demographic variables alone are not effective in marketing

use to segment green consumers. These authors stated that a combination of psychographic

and demographic variables is a better solution for the segmentation of green consumers.

Balderjahn (1988) shared the same thought process when it was stated that the predictive

power of demographic and socioeconomic variable is normally low.

Diekmann and Preisendörfer (1998) discussed the negative effect of age on environmental

consciousness and how it was in line with earlier research such as VanLiere and Dunlap (1980)

and Jones and Dunlap (1992). Diekmann and Preisendörfer (1998) stated that although

younger people are much better informed about ecological problems and show higher levels of

environmental consciousness, there is no significant effect with age on behaviour. This is in line

with many other research papers which concluded that for the younger generation, what is

being said and actual behaviour do not match often. Older people have shown to be less


18

environmentally concerned when it came to their shopping behaviour including recycling. On the

other hand, their means of transportation involved less use of automobiles, meaning less

pollution (Diekmann and Preisendörfer, 1998).

However, Gilg et al. (2004) found that age had a positive impact on green consumption, with

older age groups more likely to save their money and consume less than the younger age

groups. The more recent study of Gilg et al. (2004) might suggest that the significance of age

has increased. With the statements above to justify, this paper decided to use the demographic

factor age as a variable, and formed the third hypothesis:

H3: Age influences ecological purchase intentions

2.6 Hypotheses To summarize, the following hypotheses have been formulated based on the discussed theory:







19

Chapter 3 Methodology and Dataset

This chapter begins by introducing the conceptual framework. Subsequently, the questionnaire

and its measures will be discussed, the hypotheses will be linked to the framework, a

description of the data will be given and data analyses will be explained.

3.1 Conceptual Framework According to the theoretical background, there are several elements that could influence

ecological purchase intentions. This research proposes a conceptual framework that suggests

that ecological purchase intentions are directly influenced by three factors.

Figure 1 Conceptual Framework

The described literature has argued that environmental attitude can be an important factor to

foresee ecological purchase intentions. Fraj and Martinez (2007) for example focused on

environmental attitudes as meaningful predictors. Eilam and Trop (2012) defined environmental

attitude as a requirement for achieving environmental behaviour.

Age

Ecological Purchase Intentions

Environmental Attitude

Perceived Responsibilities


20

Perceived responsibilities can be considered as the consumer’s opinion on who is accountable

for the production and usage of eco-friendly products. These responsibilities will be measured

and tested for ecological purchase intentions. In this paper a distinction is made into corporate,

governmental and social responsibilities. Even though the concept of consumer’s perceived

responsibility was established in 1973 (Kinnear et al.), very little has been written about this

concept.

According to the literature, age is also a factor that can affect the ecological purchase intentions.

Diekmann and Preisendörfer (1998) stated that age did not have a significant effect on

ecological behaviour. Nevertheless, in a more recent study of Gilg et al. (2004), age did had a

significant impact on behaviour. To validate if the age factor is significant, the influence of age

will be tested on purchase intentions in this paper.

The goal of this thesis is to discover more about the three factors, and if they significantly affect

ecological purchase intentions. The following subchapters will discuss how these factors will be

tested.

3.2 Measures A questionnaire3 has been used to evaluate the consumer’s view about certain environmental

topics. The questionnaire is in English and it consists of 18 questions. However, 5 questions

have been disregarded due to the lack of relevance for this study. The main goal of the

questionnaire is to examine how the respondents consider the environment. This paper will test

if the opinions of the respondents are congruent with their purchasing intentions.

The first section of the questionnaire emphasizes on the general concern about the

environment. A distinction has been made between flora and fauna. Respondents are surveyed

on how they feel about these two topics. Besides questions about flora and fauna, there is also

a consumers’ awareness question. This question discusses the significance and actuality of

eco-friendly products.

In the second section eco-friendly definitions and responsibilities are argued. Via multiple

questions, the respondents are inquired about their opinion concerning the meaning of eco-

3 See appendix 1


21

friendly and who should be responsible for these types of solutions. The perceived roles of the

corporate world, the government and the consumers are measured. Furthermore, respondents

are inquired regarding the importance on how companies should act to fulfil the current trend of

eco-friendly products and services.

The third and final section contains questions that address the respondent’s environmental

intentions. Striving to be more eco-friendly and the need to talk about environmental issues are

measured. When compared with the questions of the first two sections, these questions give

insight on the thoughts that consumers have will translate into their intentions. The impact of

eco-friendly labels and age are also measured in the final section.

A five-point Likert scale has been used in the first two sections to measure the opinion based

items. The scale ranges in order from one extreme to the other, namely strongly disagree to

strongly agree. Options in the middle are disagree, neutral and agree. In the third section of the

questionnaire, besides the five-point scale, a three-point scale for yes and no answers is used

to test the environmental intentions. Lastly, age is categorized in 5 groups.

3.3 Sample and data description The data for this research was obtained via third-year students who participated in the

Consumer Behavior course in 2011 & 2012 at the Erasmus University Rotterdam. The objective

of their assignment was to measure differences on environmental topics between generations.

The students were divided into pairs. Each team collected approximately 25 respondents. In

total, 2668 valid results were collected. To enhance the validity of the samples the students

took, this research combines all the results.

The students distributed the questionnaire via various channels. E-mail and online networks like

Facebook were used. A face-to-face method was also applied by the students. For example,

students who did not follow the course were inquired at the campus. Besides Dutch students,

international students participated in the course as well. However, no nationalities and places of

residency were noted, therefore it cannot be assumed that all the respondents have a Dutch

nationality or live in Holland.


22

The questions that are important for this research are described with descriptive analyses. The

statistical program IBM SPSS, version 19, will be used to examine the collected data. Graphic

analyses of the results are made in bar charts, and are viewed in the next subchapters to assist

each analysis. Each bar chart will display the proportion distribution to each response of the

specific question. In the following figure, the relationship between the hypotheses and each

factor that influences ecological purchase intentions are linked.

Figure 2 Conceptual Framework linked with hypotheses

With the above figure giving a clear visualization of the established relationship between the

hypotheses and factors, the corresponding variables will be discussed in the following

paragraph.

3.3.1 Environmental attitude variables

In total there are 4 variables regarding environmental attitude. The first question about

environmental attitude states that an increasing amount of consumers recognizes the relevance

of taking care about ‘’mother earth’’ considering the design, production and disposing of the

purchased products. 74.7% agrees with this statement, this is in line with the increased

environmental awareness that has been discussed in the introduction.

•H1: A positive environmental attitude enhances ecological purchase intentions

Environmental Attitude

•H2a: Perceived social responsibility influences ecological purchase intentions

•H2b: Perceived corporate responsibility influences ecological purchase intentions

•H2c: Perceived governmental responsibility influences ecological purchase intentions

Perceived Responsibilities

•H3: Age influences ecological purchase intentions

Age

Ecological Purchase

Intentions


23

0,9%

2,7%

9,0%

56,4%

31,0%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 2 Caring about flora

The following two questions ask if the respondents agree with statement ‘’Caring about the flora

(vegetation) and fauna (animals) is important’’. For these questions a large number of at least

87% agrees that both topics are important. There is very little difference between these two

results. It seems that the respondents value both flora and fauna almost equally important.

Similar to the previous question this outcome can be seen as expected considering the rise in

environmental consciousness.

The final environmental attitude variable measured if the respondents felt the need to talk about

environmental issues with their family and friends. 28.3% of the respondents did not felt the

need at all. Nevertheless, the majority of the respondents did actually share their environmental

concerns.

1,5%

9,3%

14,5%

60,6%

14,1%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 1 Recognize the relevance

0,9%

1,9%

9,0%

55,0%

33,2%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 3 Caring about fauna

28,3%

52,4%

19,3%

Not at all

Sometimes

Yes

Chart 4 The need to talk


24

2,2%

10,6%

18,9%

47,5%

20,8%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 7 Social/cultural based solutions

4,2%

19,3%

20,6%

42,1%

13,8%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 5 Technology based solutions

3.3.2 Perceived responsibility variables

To measure perceived responsibilities, 6 variables have been selected. The graphs on this page

regard the section where the respondents were inquired about what they felt eco-friendliness

should have a strong focus on. Technology based is a variable for perceived corporate

responsibility.

Striking is that more respondents feel that society is responsible for eco-friendly solutions

instead of the technology bases and government based solutions. According to 68.3% of the

respondents, society should focus on eco-friendly solutions, whereas 48.1% agrees with the

government and 55.9% agrees that it should be technology based. The disagreement levels

reflect the same distribution. Chart 6 is the only variable that is linked with perceived

governmental responsibility.

6,1%

22,0%

24,7%

37,9%

9,2%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 6 Government based solutions


25

Chart 8 corresponds with the statement that the business needs to pay attention to the

environmental impact in order to meet legal requirements without disturbing their potential of

expanding market segment. 68% of the respondents agree with this statement.

Chart 9 corresponds with the statement

that the business needs to pay attention to

current production methods and

consuming behaviour of the consumers in

order to minimize the use of energy,

pollution and waste. An astonishing

number of 86.5% agrees with this

statement.

Chart 10 corresponds with the

statement that consumers are

responsible to make a change in

purchasing eco-friendly products.

70.5% of the respondents agree that

they are responsible.

2,2%

8,4%

21,4%

53,9%

14,1%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 8 Business_legal_requirements

1,0%

3,3%

9,2%

52,0%

34,5%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 9 Business_production_methods

2,1%

9,5%

17,9%

44,4%

26,1%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 10 Consumers are responsible


26

1,0%

59,6%

20,5%

12,1%

6,8%

< 17

18 - 26

27 - 40

41 - 55

> 55

Chart 11 Age

4,1%

22,7%

31,4%

34,3%

7,5%

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

Chart 12 Striving to be more eco-friendly

3.3.3 Age variable

A large majority of the respondents are between 18 and 26 years old. Explanation for this could

be that several teams surveyed their friends and other students at the campus. Only 1% of this

sample is younger than 18. Diekmann and Preisendörfer (1998) and Gilg et al. (2004) stated

that older age groups are less likely to consume eco-friendly.

3.3.4 Dependent variable

The variable that is linked to ecological purchase intentions is based on the question if the

respondent considers itself as a person who is striving to be a more eco-friendly consumer.

Almost 42% agrees with this statement and 27% disagrees. Although the percentage agree is

higher than disagree, it appears that in this study there is also a case of the consumer paradox.

In chart 10 70.5% agreed that the consumers are responsible to purchase eco-friendly.

However, compared with this chart 28.5% seem to have changed their mind/intention.


27

3.4 Data analyses In this subchapter, statistical subjects will be discussed. The statistical program IBM SPSS,

version 19, has been used to examine the collected data. Firstly, the preliminary work that is

necessary to correctly assess the data will be mentioned. From then on, various statistical tests

which have been applied will be discussed.

3.4.1 Data preparation

The adopted data was entered in excel. For this study the data has been inserted and modified

in SPSS. For the majority of the questions, a five-point Likert scale had been used in the survey.

These questions are coded as ordinal variables in SPSS. 1 for strongly disagree, 2 for disagree

– 5 for strongly agree. The remaining questions are coded as nominal variables: no as 1, do not

know/sometimes as 2 and yes as 3. Finally, age is dissected in 5 categories. To examine the

significance and influence of each age category, dummy variables (recoded into 0 and 1) have

been constructed. There were no missing values in the dataset.

3.4.2 Normal distribution

To determine which statistical tests can be used to analyse the data, the normality of the

collected data has to be assessed first. Furthermore, normal distributions are good descriptions

for random sampling and to estimate several types of chance outcomes, such as tossing a coin

many times (Moore, 2003).

‘’The normal distribution in statistics, also known as the Gaussian distribution, is defined by the

two parameters mean and standard deviation. It can be considered as a theoretical frequency

distribution for a set of variable data, usually represented by a bell-shaped curve symmetrical

about the mean’’4. Normally distributed data implies that the majority of the observations in a

sample are near the mean, whereas relatively few observations deviate to the left or right

border. The difference among these observations is measured by the standard deviation.

There are several options in SPSS to test if the data is normally distributed. In this paper a

normal probability plot will be constructed and histograms will be plotted. The normal probability

plot is a graphical method that reflects the values of the dependent variable against the

standardized values of the independent variables. If the values follow a straight linear line, it can

4 http://easycalculation.com/statistics/learn-normal-distribution.php


28

be assumed that the data is normally distributed .The histograms reflect each of the variables in

graphs with a bell-shaped curve, the data can be considered normal if the curve is symmetrical.

Besides these tests, there is also a test on skewness and kurtosis. These tests are necessary

because the earlier discussed graphical method can be interpreted in different ways. With a

perfect normal distribution both skewness and kurtosis present a value of 0. However, values

between -1 and +1 are commonly accepted (Field, 2005). Skewness shows the asymmetry and

deviation in a normal distribution. A positive skewness value, thus larger than 0, indicates that

the majority of the sample can be found on the left side of the mean, whereas a negative value

smaller than 0 indicates that the majority of the sample is one the right side of the mean.

Kurtosis is a measurement to identify a flattened or a peaked distribution. A value larger than 0

indicates a higher peak than the normal distribution, this means that the majority of the sample

can be found near the mean due to the low variation in the observations. A value of kurtosis

smaller than 0 results into a flattened peak compared to the normal distribution, this indicates

that the observations in the sample are widely spread around the mean. To simplify, skewness

indicates if the bell-shape is curved to the left or right, kurtosis indicates if the bell-shape is

flattened or peaked. The means and values of these tests can be found in table 1.

Table 1 Normal distribution

Variables Mean Std. deviation Skewness Kurtosis Recognize the relevance 3.76 0.86 -0.98 0.97 Caring about flora 4.14 0.75 -1.10 2.39 Caring about fauna 4.18 0.74 -1.11 2.57 Technology based solutions 3.42 1.08 -0.43 -0.65 Government based solutions 3.22 1.08 -0.30 -0.75 Social/cultural based solutions 3.74 0.98 -0.72 0.09 Business legal requirements 3.69 0.89 -0.81 0.66 Business production methods 4.16 0.80 -1.16 2.11 Consumers are responsible 3.83 0.99 -0.76 0.11 Striving to be more eco-friendly 3.18 1.00 -0.17 -0.65 The need to talk 1.91 0.68 0.12 -0.87 Younger than 17 0.01 0.10 9.99 97.81 18 - 26 0.60 0.49 -0.39 -1.85 27 - 40 0.20 0.40 1.46 0.15 41 - 55 0.12 0.33 2.32 3.41 Older than 55 0.07 0.25 3.43 9.75


29

According to the normality tests, 8 out of the 16 of the variables are not normal distributed.

However, the dependent variable is normally distributed. The normal probability plot and the

corresponding histogram also confirm the normality of the dependent variable related with the

independent variables. This is one of the key assumptions for using multiple regression

analysis, the corresponding graphs can be found in appendix 3.

3.4.3 Correlation analysis A correlation test measures to what extent linear relationships exists amongst the variables

(Field, 2005). The correlation describes the strength, also known as effect size, and direction of

the linear relationship. Using this analysis can determine which variables are valuable to further

examine. In this paper it will be measured to what extent the independent variables (X)

associate with the dependent variable (Y).

The correlation analysis results into a coefficient that can be positive as well as negative. The

value lies between -1 and 1. A coefficient of 0 indicates that there is no relationship at all

between the variables, and a value of 1 or -1 means there is a perfect positive or negative

relationship. For example, if the correlation coefficient between caring about fauna and caring

about flora is 1, it means that caring about fauna implies that the respondent also cares about

the flora.

Pearson’s correlation coefficient will be used to measure the relationships, also known as

Pearson’s r. The coefficient is useful because it provides an unbiased measure of the

importance of an effect (Field, 2005). In his book Field also states commonly accepted numbers

for effect size:

Small effect r ≈ 0.10

Medium effect r ≈ 0.30

Large effect r ≈ 0.50

In SPSS the significance and effect size (r) of correlations can be calculated. A relationship

between variables exists if the correlation coefficients are significant.

Person’s formula can be found on the next page, where µx refers to the means of the

independent variables whereas µy reflects the mean of the dependent variable. σx and σy

reflect the standard deviation.


30

(3.1) Pearson’s correlation coefficient formula

풓 =퐶푂푉푥푦σxσy

= ∑(푋푖 − μx)(푌푖 − μy)

(푁− 1)σxσy

3.4.4 Multiple regression analysis

While correlation measures the effect size of a linear relationship among two variables,

regression goes a step further. It is believed that regression analysis is probably the most widely

applied statistical method for forecasting and financial analysis. With regression analysis it is

possible to predict one variable from another. A correlation coefficient reflects how strong a

relationship between two variables is, regression analysis constructs a predictive model based

on the data. Through this model values of the dependent variable can be predicted from the

independent variables (Field, 2005).

In this paper it will be examined which variables can indicate/predict ecological purchase

intentions. As mentioned earlier, this study has 16 variables including the dependent variable.

Hence the predictive power of 15 variables will be tested. To determine if these variables

influence effect on ecological purchase intentions, a significance level, also known as p-value,

of 5% will be applied. This level suggests that only if it is certain by 95% that the result is

genuine, it can be accepted as significant (Field, 2005).

In SPSS Linear Regression will be selected to construct the regression model.

To clarify how multiple regression analyses work, the formula can be found below. In this

research the dependent variable is ordinal, so it is not possible to reproduce the same formula

for the data. However, the results can predict the influence on ecological purchase intentions

(3.2) Multiple regression formula

Y = β0 + β1X1 + β2X2 + ……. βnXn + ε

Where:

Y = Dependent variable

Xn = Independent variables

β0 = Intercept/starting point of the model

βn = Coefficients/estimates belonging to each variable x for the individual i

ε = error or residue of the model


31

To use regression analysis, several assumptions have to be met/true:

Normal distribution

This assumption has already been tested and fulfilled by the normal probability plot,

histogram, skewness and kurtosis. Nevertheless, from a statistical view it is

recommended that all variables used in the model are normally distributed.

Lack of multicollinearity

A risk in many datasets is multicollinearity, this stands for a high correlation between

independent variables. In the previous subchapter it was mentioned that a high

correlation is favourable, however this only applies to the correlation between a

dependent and independent variable. A strong correlation between independent

variables can result into an arbitrary regression model. In this the case both variables

practically explain the same variance in the dependent variable due to the high

standard error and low coefficient. Consequently, the importance of the variables in

the model cannot be determined. Multicollinearity can be measured in SPSS with the

option collinearity diagnostics. This option produces a variance inflation factor (VIF).

According to several researchers that Field (2005) states in his book, VIF values

above 10 and below 0.2 are worthy of concern. In this study the values are between

1 and 2, the numbers can be found in appendix 5.

Linear relationships among dependent and independent variables

This assumption has already been tested and fulfilled by the normal probability plot

and correlation analysis.

Independent errors

For any succeeding observations in regression analysis, the residuals should be

uncorrelated (Field, 2005). This problem is also known as autocorrelation and it often

occurs with time series in regression models. It can wrongfully enlarge regression

estimates and increase p values. For this assumption Durbin-Watson is the test to

use in SPSS. The number of this test varies between 0 and 4. A number near 2 is

commonly accepted, and implies that there is very little correlation between

residuals. In this study the Durbin-Watson number is 1.7, hence this assumption has

been met.


32

0,24

0,33

0,32

0,04

0,08

0,16

0,05

0,19

0,28

0,41

-0,16

0,08

0,11

0,05

Recognize the relevance

Caring about flora

Caring about fauna

Technology based solutions

Government based solutions

Social based solutions

Business legal requirements

Business production methods

Consumers are responsible

Need to talk

18 - 26

27 - 40

40 - 55

Older than 55

Chart 13 Correlations with the strive to be an eco-friendly consumer

Chapter 4 Results

In this chapter the statistical results and importance of the correlation analysis and regression

analysis will be discussed. Subsequently, at the end of this chapter the hypotheses will be

tested by means of these results.

4.1 Correlation results The chart underneath shows the correlations coefficients of the independent variables

associated with the dependent variable. This analysis can help us understand which individual

independent variable is important to the variable of ecological purchase intention. Every

displayed variable in the chart is significant, so those variables are related to the intentions to be

a more eco-friendly consumer. Of all the variables selected for this study, the only exception is

the age category younger than 17. This variable has no significant relationship with the

dependent variable.


33

The other age category of 18 – 26 appears to be the only variable that has a negative

relationship with the dependent variable. This implies that an increase in that age category

results into a decrease in the strive to be an eco-friendly consumers. However, with a coefficient

of –0.16 the effect size is relatively small as discovered from the previous chapter. The small

effect size also implies for the other age categories, where respondents between 40 – 55 years

old appear to have the strongest association versus the respondents of 55 years and older with

the lowest association of the age categories.

Most variables regarding the perceived responsibilities similarly show small effect sizes related

to ecological purchase intentions. The statement that eco-friendly means a strong focus on

technology based solutions has the lowest effect of all variables on ecological purchase

intentions. The only variable directly linked to governmental responsibility also has a low

association with ecological purchase intentions. On the other hand, the statement that

consumers are responsible to make a change in purchasing eco-friendly products has a

medium effect size with a coefficient of 0.28. This is the strongest association within perceived

responsibilities, and certainly worth examining.

From all the selected ones in this model, the variables linked to environmental attitude appear to

have the largest effect size on ecological purchase intentions. The statement that an increasing

amount of consumers recognizes the relevance of taking care about ‘’mother earth’’ considering

the design, production and disposing of purchased products has the lowest association within

this set. Feeling the need to talk about environmental issues with family/friends has the highest

association with ecological purchase intentions of all variables in this paper. With a coefficient of

0.41 the effect size is exactly between medium and large, respectively 0.3 and 0.5. This implies

that the need to talk is an important variable regarding ecological purchase intentions.

The correlation amongst all the variables can be found in appendix 4. As expected the

correlation between caring about flora and fauna is the highest of all, nonetheless the VIF is

acceptable for using both variables in the regression analysis.

4.2 Multiple regression results Although correlation analysis is useful to study the different variables, the analysis cannot

determine in which direction the dependent variable will follow when all variables are tested

together. In this subchapter we will discuss the predictive power of the significant variables.


34

After fulfilling the required assumptions, a regression model with all selected variables is

constructed. The significant variables with their corresponding coefficients can be found in table

2.

Table 2 Significant regression results Variables β

Recognize the relevance 0.09 Caring about flora 0.14 Caring about fauna 0.15 Business legal requirements -0.05 Business production methods 0.06 Consumers are responsible 0.13 Need to talk 0.43 27 - 40 0.15 40 - 55 0.20

Every variable concerning the environmental attitude in this model has a significant effect on

ecological purchase intentions. These variables positively influence the strive to be a more eco-

friendly consumer. The predictive power of the β’s, or coefficients, do vary a lot. The statement

that consumers recognize the relevance has the lowest coefficient within this set, this suggests

that the variable has the least influence on ecological purchase intentions within environmental

attitude. Caring about flora and fauna appear to have a positive effect that is almost similar, this

not surprising after studying the results of the questionnaire. The need to talk about

environmental issues proves yet again to be a very important variable for this study. With a

coefficient of 0.43 it has the highest influence on ecological purchase intentions within this

model.

To measure the influence of perceived responsibilities, 6 variables have been used in this study,

3 of those appear to have a significant effect in this model. The only variable for measuring

perceived governmental responsibility is not significant. For perceived corporate responsibility 2

out of 3 variables are significant. The variable that does not have an influence in this model is

the statement that eco-friendly means a strong focus on technology based solutions. Striking is

the negative influence of the statement that the business needs to pay attention to the

environmental impact in order to meet legal requirements. This means that agreeing with

statement results into a decrease in ecological purchase intention. Although the coefficient, and


35

therefore the predictive power, is relatively low, this variable has a significant value. Perceived

social responsibility has 1 significant variable out of 2. The insignificant variable is the statement

that eco-friendly means a strong focus on social/cultural based solutions. However, the other

statement that consumers are responsible to make a change in purchasing eco-friendly

products, is significant and has a predictive power of 0.13 which can be considered as

influential.

Of the 5 age categories, 3 groups appear to be insignificant in this model. The groups of 27 - 40

and 40 – 55 have a significant influence on ecological purchase intentions with respectively

coefficients of 0.15 and 0.20. This implies that the category of 40 – 55 has a stronger intention

than the younger group. In fact, the specific category is the second most powerful predictor in

the regression model. The other variables and a total overview of the regression model can be

found in appendix 5.

4.3 Overview of results In this subchapter the hypotheses and independent variables are linked in order to indicate the

consequences of the previous discussed results.


Recognize the relevance is significant with a β of 0.09

Caring about flora is significant with a β of 0.14

Caring about fauna is significant β of 0.15

Need to talk is significant with a β of 0.43

This hypothesis is supported, all variables are significant.


Social/cultural based solutions is not significant

Consumers are responsible is significant with a β of 0.13

This hypothesis is supported. Despite the insignificance of one variable, the correlation and β of

the other variable appear to be significant enough to affect ecological purchase intentions.

Recommended is to further investigate this topic, and if possible add more variables to

determine the importance of this topic.


36


Technology based solutions is not significant

Business legal requirements is significant with a β of -0.05

Business production methods is significant with a β of 0.06

This hypothesis is supported because 2 out of 3 variables are significant in the regression

model. Nevertheless, the overall effect of corporate responsibility appears to be small.

Recommended is to further investigate this topic, and if possible add more variables to

determine the importance of this topic.


Government based solutions is not significant

This hypothesis is rejected. However, further investigation and additional measurement

variables are recommended. In the literature the role of the government seemed influential to

support environmentally friendliness.


Younger than 17 is not significant

18 – 26 is not significant

27 – 40 is significant with a β of 0.15

40 – 55 is significant with a β of 0.20

Older than 55 is not significant

This hypothesis is supported. Even though the majority of the age categories are insignificant,

two age categories do positively influence ecological purchase intentions. The outcome is

sufficient to accept the hypothesis.


37

Chapter 5 Conclusion

The following research question was formulated at the beginning of this paper:

“Do consumers value a sustainable environment and which factors affect their ecological purchase intentions?”

To measure if consumers value a sustainable environment, the answers of both questions

caring about the flora and fauna will be studied. These questions have been discussed in

chapter 3.3.1, to recall 87% of the respondents agreed that both topics are important, while

70.5% agrees that consumers themselves are responsible for purchasing eco-friendly products.

Based on these percentages it can be assumed that they do value a sustainable environment.

Nevertheless, compared with the level of agreement with the dependent variable, only 42%

strives to eco-friendly consumption. This is in line with the consumer paradox theories of

Diekmann and Preisendörferer (1998), Carrington et al. (2010), and Grimmer and Bingham

(2013). They all found inconsistencies between society’s environmental attitudes and their

behaviour. To conclude, consumers say that they value a sustainable environment, however

only half of them behave this way.

To answer the second part of the main question, the sub research questions will be discussed

assisted by the literature and results.

Does a positive environmental attitude affect ecological purchase intentions?

A positive environmental attitude proves to be an influential indicator for ecological purchase

intentions in this research. Fraj and Martinez (2007), and Eliam Trop (2012) had similar findings

regarding the predictive power of environmental attitudes. In the study of Kinnear et al. (1973)

attitudes also served as indicators for ecologically-conscious purchasing.

Within this study all the selected variables for environmental attitudes have a significant effect

on ecological purchase intentions. Feeling the need to talk about environmental issues with

family and friends appears to be a powerful predictor for ecological purchase intentions, this

variable has the highest coefficient of the regression model.


38

Do perceived responsibilities affect ecological purchase intentions?

Chen and Chai (2010), and Mei et al. (2012) mention that the government should initiate and

promote sustainability for their society. The respondents of this study disagree, perceived

governmental responsibility does not affect ecological purchase intentions. Only one variable is

used in this study, it is desirable if more are added.

The results show a partial effect on perceived social responsibilities. At the same time, this

effect is the strongest of all entities with perceived responsibilities. The variable consumers are

responsible is significant and the correlation coefficient is relatively high, hence perceived social

responsibility affects ecological purchase intentions.

The same applies for perceived corporate responsibilities, 2 out of 3 variables are significant.

Nevertheless, the predictive power of this factor is questionable due to the negative and positive

coefficients with almost the same value.

Does age influences ecological purchase intentions?

Diekmann and Preisendörfer (1998) did not found a significant effect with age on environmental

behaviour. They also stated that older people have shown to be less environmentally concerned

when it came to their shopping behaviour. However, Gilg et al. (2004) found that age had a

positive impact on green consumption. In this research the younger age groups also consumed

more eco-friendly products.

Similar to Gilg et al.(2004), in this study a positive influence of age on ecological purchase

intentions is established. The respondents between 27 – 40 and 40 – 55 showed a significant

effect. In this study the influence of the older group is larger.

5.1 Limitations A major limitation is that this research design was largely adapted onto the available

questionnaire and available dataset. A crucial shortcoming is that some themes have been left

untouched in this questionnaire. For instance, there are very little psychographics and no

demographics of the respondents besides age. These data can help gaining a better

understanding of the ecological consumer. Even though the statements of Balderjahn (1998)

and Thompson et al. (2010) state that the predictive power of demographics is low, more recent

studies of Mei et al. (2012) and Ottmann (2011) segment the ecological consumers based on

demographic and psychographic variables. Both studies seem to agree that females are more

likely to consume eco-friendly products.


39

Another limitation might be that some student teams used the face-to-face method for the

survey. A major disadvantage of this method is that the presence of the interviewers might

encourage social desirable answers rather than a respondent’s truthful answers (Duffy et al.

2005). With this study on ecological intentions the answers the respondents gave, might be

biased towards environmental conscious. The number of respondents that were surveyed by

the face-to-face method is not known, thus it cannot be determined how many of them might not

answered truthfully so they do not seem oblivious to the environment.

Finally, multiple regression analysis is used while not all variables are normally distributed.

Although the results of the normal probability plot and histogram justified the applied method, in

the statistical field is preferred that all the variables for regression are normally distributed. The

largest distortions occurred in the age categories. To prevent this in the future it is wise to

approach and record an equal amount of these groups.

5.2 Recommendations for further research A recommendation is to expand research on the need to talk about environmental issues. This

has proven to be a strong predictor in this model. If this variable appears to be significant in

other studies, it might be a useful variable to utilize in the academic and managerial field. In

addition, demographics and psychographics should be added in the research model to gain a

better understanding of the consumer.

Perceived responsibilities might provide new insights in this field. In this study a few variables

that are linked to these responsibilities have significant outcomes. Nevertheless, the predictive

powers of these variables appear to be low. To determine if perceived responsibilities can

contribute to this field, it is advisable to conduct a study with more variables per entity and

determine if the influence is similarly significant.

Eco-friendly labels might also be predictors for ecological purchase intentions. In the survey

there was a question about these labels. Respondents were asked if, according to them, eco-

friendly labels on shopping goods will improve the environment. The majority responded

positively, and this resulted into a significant variable. In appendix 5 an additional regression

model with the eco-friendly label variable is constructed. Due to the magnitude of this subject,

this variable has not been discussed in this paper.


40

References Papers

Ajzen, I. (1985) ''From intentions to actions: a theory of planned behaviour'', in Kuhl, J. and Beckmann, J. (Eds),

Action-Control:From Cognition to Behaviour, Springer-Verlag, Heidelberg; pp. 11 – 39

Ajzen, I. (1991) ''The Theory of Planned Behavior'', Organizational Behavior and Human Decision Processes 50;

pp. 179 - 211

Ajzen, I., Timko, C., & White, J.B. (1982) ''Self-monitoring and the attitude-behavior relation'', Journal of Personality

and Social Psychology 42; pp. 426 - 435

Balderjahn, I. (1988) ''Personality Variables and Environmental Attitudes as Predictors of Ecologically

Responsible Consumption Patterns'', Journal of Business Research 17; pp 51 - 56

Bandhura, A., Adams, N.E., Hardy, A.B., & Howells, G.N. (1980) ''Tests of the generality of self-efficacy theory'',

Cognitive Therapy and Research 4; pp. 39 - 66

Barr, S. (2003) ''Strategies for Sustainability: Citizens and Responsible Environmental Behaviour, Area Vol. 35 No.

3; pp. 227 - 240

Brooker, G. (1976) ''The Self-Actualizing Socially Conscious Consumer'', Journal of Consumer Research, Vol. 3,

No. 2; pp. 107 - 112

Chen, T. B., & Chai, L. T. (2010) ''Attitude towards the environment and green products: Consumers perspective'',

Management Science and Engineering 4; pp. 27 - 39

Chen, Y. S. & Chang, C.H. (2012) ''Enhance green purchase intentions: The roles of green perceived value, green

perceived risk, and green trust'', Management Decision Vol. 50 No. 3; pp. 502 - 520

Cohan, P. S. (2009). Use Peer Pressure To Sell Your Product. Retrieved from: www.financialexecutives.org

Daido, K (2004) ''Risk-averse agents with peer pressure'', Applied Economics Letters; pp. 383 – 386

Derksen, L. & Gartrell, J. (1993) ''The Social Context of Recycling'', American Sociological Review 58; pp. 434 -

442

Diekmann, A. & Preisendörfer, P. (1998) ''Environmental Behavior: Discrepancies Between Aspirations And

Reality'', Rationality and Society Vol. 10; pp. 79 - 102

Diekmeyer, P. (2008) ''Bribery in public procurement: protecting your company from corruption''


41

Duffy, B., Smith, K., Tehanian, G. & Bremer, J. (2005) ‘’Comparing data from online and face-to-face surveys’’,

International Journal of Market Research Vol. 47; pp. 615 - 639

Eilam, E. & Trop, T. (2012) ''Environmental Attitudes and Environmental Behavior-Which Is the Horse and Which Is

the Cart?'', Sustainability 2012, 4; pp. 2210 - 2246

Fishbein, M., & Ajzen, I. (1975) ''Belief, attitude, intention and behavior: An introduction to theory and research

reading'' MA: Addison-Wesley

Fraj, E. & Martinez, E. (2007) ''Ecological consumer behaviour: an empirical analysis'', International Journal of

Consumer Studies 31; pp. 26 – 33

Gilg, A., Barr, S. & Ford, N. (2005) ''Green consumption or sustainable lifestyles? Identifying the sustainable

consumer'', Futures 37; pp. 481 - 504

Grimmer, M. & Bingham, T. (2013) ''Company environmental performance and consumer purchase intentions'',

Journal of Business Research 66; pp. 1946 - 1953

Guagnano, G.A., Stern, P.C. & Dietz, T. (1995) ''Influences on attitude-behavior relationships: a neutral experiment

with kerbside recycling'', Environment and Behavior 27; pp. 699 - 718

Haron. S. A., Paim. L., & Yahaya. N. (2005) ‘’Towards sustainable consumption: an examination of environmental

knowledge among Malaysians’’, International Journal of Consumer Studies, 29(5); pp. 426 – 436

Henion, K.E. & Wilson, William H. (1976) ''The Ecologically Concerned Consumer and Locus of Control, in

Ecological Marketing'', Karl E. Henion and Thomas C. Kinnear, eds. American Marketing Association Series,

Austin, Tex; pp. 131 - 144

Jones, R.E. & Dunlap, R.E. (1992) ''The Social Bases of Environmental Concerns: Have They Changed over

Time?'', Rural Sociology 57; pp. 28 - 47

Kalafatis, S.P., Pollard. M, East, R., Tsogas, M.H. (1999) ''Green marketing and Ajzen's theory of planned

behaviour: a cross-market examination'', Journal of Consumer Marketing, Vol. 16 No.5; pp. 441- 460

Kinnear, T.C., & Taylor, J.R. (1973) ''The Effect of Ecological Concern on Brand Perceptions'', Journal of Marketing

Research; pp. 191 - 197

Lee, C. and Green, R.T. (1991) ''Cross-cultural examination of the Fishbein behavioural intentions model'', Journal

of International Business Studies Vol. 22 No. 2; pp. 289 - 305


42

Lu, Y., Zhao, L. and Wang, B. (2010), “From virtual community members to C2C e-commerce buyers: Trust in

virtual communities and its effect on consumers’ purchase intention”, Electronic Commerce Research and

Applications, Vol. 9 No. 4; pp. 346 - 360.

Madden, T. J., Ellen, P.S. & Ajzen, I. (1992) ''A Comparison of the Theory of Planned Behavior and the Theory of

Reasoned Action'', Personality and Social Psychology Bulletin, Vol. 18 No. 1; pp. 3 - 9

McIntosh, A. (1991) ''The impact of environmental issues on marketing and politics in the 1990s'', Journal of Market

Reseatch Society, Vol. 33 No. 3; pp. 205 - 217

Mei, O.J., Ling. K.C. & Piew, T.H. (2012) ''The Antecedents of Green Purchase Intention among Malaysian

Consumers'' , Asian Social Science; Vol. 8, No. 13; pp. 248 - 263

Mostafa, M. M. (2007) ''Gender differences in Egyptian consumers green purchase behavior: The effects of

environmental knowledge, concern and attitude'', International Journal of Consumer Study 31; pp. 220 - 229.

Oreg, S. & Katz-Gerro, T. (2006) ''Prediciting Proenvironmental Behavior Cross-Nationally Values, the Theory of

Planned Behavior and Value-Belief-Norm Theory'', ENVIRONMENT AND BEHAVIOR, Vol. 38 No. 4; pp. 462 - 483

Renfro, L. A. (2010) ''Green business operations and green marketing'', Gatton Student Research Publication, 2.

Stern, P.C., Dietz, T. & Guagnano, G.A. (1995) ''The new ecological paradigm in social-psychological context'',

Environment and Behavior 27; pp. 723 - 743

Tapon, F. and Leighton, T. (1991), ''Green as strategy: lessons from the chemical industry'', Strategic Management

Society; pp. 23 – 26

Thompson, D.W., Anderson, R.C., Hansen, E.N. & Kahle, L.R. (2010) ''Green Segmentation and Environmental

Certification: Insights from Forest Products'', Business Strategy and the Environment 19; pp. 319 - 334

Van Liere, K.D. & Dunlap, R.E. (1980) ''The Social Bases of Environmental Concern: A Review of Hypotheses,

Explanations and Empirical Evidince'', Public Opinion Quarterly 44; pp. 181 - 197

Wray-Lake, L., Flanagan, C.A. & Osgood, D.W. (2010) ''Examining Trends in Adolescent Environmental Attitudes,

Beliefs, and Behaviors Across Three Decades'', Environment and Behavior Vol. 42 No.1; pp. 65 – 85


43

Books Charter, M. (1992) ''Greener Marketing: A Responsible Approach to Business’’, Greenleaf, Sheffield

Field, A. (2005) ‘’Discovering Statistics Using SPS’’ Second edition, Sage Publications

Moore, D.S., McCabe, G.P., Duckworth, W.M. & Sclove, S.L. (2003) ‘’The Practice of Business Statistics, Using

data for decisions’’, W.H. Freeman and Company

Ottmann, J.A. (2011) ‘’The New Rules of Green Marketing. Strategies, Tools and Inspiration for Sustainable

branding’’ Greenleaf Publishing


44

Appendix

Appendix 1: Questionnaire Q1: An increasing amount of consumers recognizes the relevance of taking care about ‘’mother earth’’ considering the design, production and disposing of the purchased products. Do you agree or disagree? Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q2: What is your opinion about the statement? ‘’Caring about the flora (vegetation) is important’’ Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Why or why not? Please mention three points Point 1: ……………………….. Point 2: ……………………….. Point 3: ……………………….. Q3: What is your opinion about the statement? ‘’Caring about the fauna (animals) is important’’ Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Why or why not? Please mention three points Point 1: ……………………….. Point 2: ……………………….. Point 3: ……………………….. Q4: Have you heard about any problems caused by human consumption that affect the environment? Please mention three problems. Problem 1: ……………………….. Problem 2: ……………………….. Problem 3: ……………………….. Q5: The driving forces to sustainable marketing has led to eco-innovations in the field of products and services. More and more consumers want to know what ‘’eco-friendly’’ really means, Consider the next three statements. Q5A: ‘’Eco-friendly’’ means a strong focus on technology based solutions. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q5B: ‘’Eco-friendly’’ means a strong focus on government based solutions. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □


45

Q5C: ‘’Eco-friendly’’ means a strong focus on social/cultural based solutions. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q6: The trend on the demand side of the food industry and food chains(shops) shows that consumers are more and more concerned with ‘eco-friendly’ food products. Consequently the industry and the shop chains have to change their methods of production and selling of the products. Where do you think the business should start to make the change? Consider the next three statements: Q6A: The business needs to pay attention to the environmental impact in order to meet legal requirements without disturbing their potential of expanding market segment. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q6B: The business needs to current business production methods and consuming behaviour of the consumers in order to minimize the use of energy, pollution and waste. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q6C: Consumers are responsible to make a change in purchasing ‘eco-friendly’ products.. Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q7: One of the ideas for creating a better environment is to change the behaviour of consumers towards more ‘eco-friendliness’ or sustainable purchasing. Q7A: Do you consider yourself as a person who is striving to be a more ‘eco-friendly’ consumer? Strongly disagree Disagree Neutral Agree Strongly agree □ □ □ □ □ Q7B: Do you feel the need to talk about environmental issues with your family/friends? Not at all Sometimes Yes □ □ □ Q7C: Do you think ‘eco-friendly’ labels on shopping goods will improve the environment? No Don’t know Yes □ □ □ Q8: Do you prefer organic wine/beer above a fair trade wine/beer? No Don’t know Yes □ □ □


46

Q9: What does it mean to say that something is ‘natural’? ………………………………………………………......... Q10: What should people do to live in harmony with nature? ……………………………………………………………… Q11: Suppose you are the minister of environmental affairs, what would be your main policy goals? ………………………………………………………………. Q12: What is the age of the respondent? 8 - 17 18 - 26 27 - 40 41 - 55 Older than 55 □ □ □ □ □

Appendix 2: Frequency tables SPSS output

Consumers recognize the relevance of taking care of ''mother earth''

Caring about the flora (vegetation) is important Frequency Percent Frequency Percent

Valid Strongly Disagree

40 1.5


23 .9

Disagree 248 9.3

Disagree 73 2.7

Neutral 387 14.5

Neutral 240 9.0

Agree 1617 60.6

Agree 1505 56.4

Strongly Agree

376 14.1

Strongly Agree

827 31.0

Total 2668 100.0

Total 2668 100.0

Caring about the fauna is important

Eco-friendly means a strong focus on technology

based solutions Frequency Percent

Frequency Percent


24 .9


112 4.2

Disagree 52 1.9

Disagree 514 19.3

Neutral 239 9.0

Neutral 550 20.6

Agree 1467 55.0

Agree 1124 42.1

Strongly Agree

886 33.2

Strongly Agree

368 13.8

Total 2668 100.0

Total 2668 100.0


47

Eco-friendly means a strong focus on government based solutions

Eco-friendly means a strong focus on social/cultural based solutions

Frequency Percent

Frequency Percent Valid Strongly

Disagree 164 6.1


58 2.2

Disagree 587 22.0

Disagree 283 10.6

Neutral 660 24.7

Neutral 505 18.9

Agree 1011 37.9

Agree 1267 47.5

Strongly Agree

246 9.2

Strongly Agree

555 20.8

Total 2668 100.0

Total 2668 100.0



Frequency Percent


Disagree 58 2.2


27 1.0

Disagree 225 8.4

Disagree 88 3.3

Neutral 571 21.4

Neutral 245 9.2

Agree 1438 53.9

Agree 1387 52.0

Strongly Agree

376 14.1

Strongly Agree

921 34.5

Total 2668 100.0

Total 2668 100.0

Consumers are responsible to make a change in purchasing eco-friendly products

Do you consider yourself as a person who is striving to be a more 'eco-friendly' consumer?

Frequency Percent


Disagree 56 2.1


110 4.1

Disagree 253 9.5

Disagree 605 22.7

Neutral 478 17.9

Neutral 837 31.4

Agree 1184 44.4

Agree 915 34.3

Strongly Agree

697 26.1

Strongly Agree

201 7.5

Total 2668 100.0

Total 2668 100.0


48

Do you feel the need to talk about environmental

issues with your family/friends?

Do you think 'eco-friendly' labels on shopping goods will improve the environment?

Frequency Percent

Frequency Percent Valid Not at all 755 28.3

Valid No 518 19.4

Sometimes 1399 52.4

Do not know

827 31.0

Yes 514 19.3

Yes 1323 49.6

Total 2668 100.0

Total 2668 100.0

Appendix 3: Normal distribution plots & table Normal Probability Plot


49

Descriptive Statistics

N Mean Skewness Kurtosis

Statistic Statistic Statistic Statistic Consumers recognize the relevance of taking care of ''mother earth''

2668 3,76 -,979 ,971

Caring about the flora (vegetation) is important 2668 4,14 -1,104 2,386

Caring about the fauna is important 2668 4,18 -1,112 2,566

Eco-friendly means a strong focus on technology based solutions

2668 3,42 -,432 -,654


2668 3,22 -,299 -,754


2668 3,74 -,715 ,085

Business_legal_requirements 2668 3,69 -,813 ,657

Business_production_methods 2668 4,16 -1,160 2,105


2668 3,83 -,761 ,112

Do you consider yourself as a person who is striving to be a more 'eco-friendly' consumer?

2668 3,18 -,171 -,653

Do you feel the need to talk about environmental issues with your family/friends?

2668 1,91 ,116 -,867

Younger than 17 2668 ,0097 9,987 97,811

18 - 26 2668 ,5963 -,393 -1,847

27 - 40 2668 ,2046 1,465 ,146

41 - 55 2668 ,1211 2,325 3,406

Older than 55 2668 ,0682 3,427 9,753

Valid N (listwise) 2668


Appendix 4: Correlation table

Recognize the relevance

Caring about flora

Caring about fauna







Striving to 'eco-friendly'

Need to talk

Caring about flora

.361**

Caring about fauna

.342** .650**


.080** .078** .086**


.038* .100** .120** .348**


.140** .196** .204** .068** .233**


.114** .149** .129** .148** .145** .051**


.195** .277** .294** .104** .077** .181** .145**


.167** .236** .242** .056** .053** .188** .112** .198**

Striving to 'eco-friendly'

.238** .334** .324** .041* .083** .158** .047* .192** .276**

Need to talk .177** .278** .235** ,026 .051** .158** .084** .147** .218** .410**

Age .093** .100** .103** ,021 .092** ,027 ,031 .042* .101** .153** .163**

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).


51

Appendix 5: Regression tables Coefficientsa The insignificant variables are marked

Model

Unstandardized Coefficients

t Sig.

Collinearity Statistics

B Std. Error VIF 1 (Constant) ,076 ,142 ,535 ,592


,089 ,021 4,184 ,000 1,205

Caring about the flora (vegetation) is important ,136 ,030 4,491 ,000 1,884

Caring about the fauna is important ,146 ,030 4,789 ,000 1,844


-,009 ,017 -,537 ,591 1,167


,030 ,017 1,743 ,082 1,224


,018 ,018 ,997 ,319 1,149

Business_legal_requirements -,049 ,019 -2,529 ,011 1,072

Business_production_methods ,060 ,022 2,671 ,008 1,166


,134 ,018 7,502 ,000 1,141


,431 ,026 16,502 ,000 1,154

Younger than 17 ,138 ,171 ,809 ,419 1,019

27 - 40 ,154 ,043 3,583 ,000 1,088

41 - 55 ,203 ,053 3,816 ,000 1,090

Older than 55 ,088 ,068 1,297 ,195 1,060

a. Dependent Variable: Do you consider yourself as a person who is striving to be a more 'eco-friendly' consumer?

Model Summaryb

Model R R

Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 .520a ,270 ,266 ,858 1,700


52

Below the regression results with the eco-friendly labels variable included.

Coefficientsa

Model

Unstandardized Coefficients

t Sig. B Std. Error

1 (Constant) -.008 .142 -.054 .957


.082 .021 3.872 .000

Caring about the flora (vegetation) is important .131 .030 4.357 .000

Caring about the fauna is important .140 .030 4.607 .000


-.014 .017 -.851 .395


.030 .017 1.756 .079


.016 .018 .882 .378

Business_legal_requirements -.051 .019 -2.643 .008

Business_production_methods .060 .022 2.697 .007


.121 .018 6.684 .000


.419 .026 16.086 .000

Do you think 'eco-friendly' labels on shopping goods will improve the environment?

.113 .022 5.057 .000

Younger than 17 .157 .170 .925 .355

27 - 40 .158 .043 3.703 .000

41 - 55 .186 .053 3.511 .000

Older than 55 .082 .068 1.215 .225

a. Dependent Variable: Do you consider yourself as a person who is striving to be a more 'eco-friendly' consumer?

ecological purchase intentions

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